Results 91 to 100 of about 3,745,728 (280)
Multi-Objective Unsupervised Feature Selection and Cluster Based on Symbiotic Organism Search
Unsupervised learning is a type of machine learning that learns from data without human supervision. Unsupervised feature selection (UFS) is crucial in data analytics, which plays a vital role in enhancing the quality of results and reducing ...
Abbas Fadhil Jasim AL-Gburi +3 more
doaj +1 more source
The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
This paper proposes a novel hybrid approach that combines unsupervised feature extraction through clustering and unsupervised feature selection for data reduction, specifically targeting high-dimensional data.
David Gutman +3 more
doaj +1 more source
Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling
This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou +4 more
wiley +1 more source
From Lab to Landscape: Environmental Biohybrid Robotics for Ecological Futures
This Perspective explores environmental biohybrid robotics, integrating living tissues, microorganisms, and insects for operation in real‐world ecosystems. It traces the leap from laboratory experiments to forests, wetlands, and urban environments and discusses key challenges, development pathways, and opportunities for ecological monitoring and ...
Miriam Filippi
wiley +1 more source
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
CGUFS: A clustering-guided unsupervised feature selection algorithm for gene expression data. [PDF]
Xu Z +6 more
europepmc +1 more source
CD9+ B Cells Induce T Follicular Helper Cell Apoptosis to Regulate Germinal Center Regression
A unique subset of CD9+ B cells regulates germinal center B (GC‐B) cell regression by inducing T follicular helper (Tfh) cell apoptosis through multiple signaling pathways, such as ALCAM‐CD6. FOXP1 plays a key role in GC‐B cell differentiation. These findings clarify mechanisms of GC degeneration and termination and offer potential targets for adenoid ...
Wenjing Liao +27 more
wiley +1 more source
Unsupervised Feature Selection with Local Structure Learning
Conventional graph-based unsupervised feature selection approaches carry out the feature selection requiring two stages: first, constructing the data similarity matrix and next performing feature selection.
Feiping Nie +5 more
core +1 more source

